This repository contains code how to build job recommendation engine using Kaggle 'Job Recommendation Challenge' dataset
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Updated
Apr 11, 2018 - Jupyter Notebook
This repository contains code how to build job recommendation engine using Kaggle 'Job Recommendation Challenge' dataset
Aim is to come up with a job recommender system, which takes the skills from LinkedIn and jobs from Indeed and throws the best jobs available for you according to your skills.
Our solution for Recsys Challenge 2017.
Several baseline models and PJFNN on Job Recommendation Challenge
Job recommendation system using NLP, in which a user’s description is evaluated via a trained NLP model and jobs are suggested based on the similarities between the user’s skill set and the job’s required skill set. Jobs are scraped from various trustworthy sites in real time using Selenium and stored in a database.
This is base-line approach for building job recommendation engine
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